This is an old concept, applied to the world of cloud computing.

The architecture can be visualized with a simple three tier drawing. In practice, there are usually sub-tiers in the middle.

Why use a business rules engine to create an online (cloud-based) marketing database?

The schema is specially structured to be easy to work with for report developers.

Using the Rules Engine prevents your encountering the shortcomings of dashboarding tools when they attempt to do conversion and transformation (The ETL layer).

Google Data Studio and Microsoft Power BI
Dashboarding tools download from raw data sources. Then the report developer must implement business logic within the report to convert it from raw data into “information.”.

Your business logic implementation will be in the scope of a single report, which means the logic must be cloned for every report ever produced. This is semi-efficient when you’re creating the first suite of reports, but it becomes a maintenance nightmare when business rules evolve.

Client tools need the full dataset to do ETL type tasks. This is resource and time intensive because it’s driven by a user interface not an automated engine. In certain volumes, it will exceed the limits of the tool but you may not discover that till you’ve committed to the approach.

It will be difficult for your successors to take the project over. Although job security is nice, you can say goodbye to career growth or taking holidays when you want to, if you implement your business rules in the visualization layer.

Google Sheets and Excel
Spreadsheets are light weight data processors, best used for ad hoc reports and analysis, or for sharing information among a small number of trained users. Spreadsheets can’t handle large volumes of data and spreadsheet functions are error prone, difficult to setup and run. If something changes in the incoming data, someone is required to debug a complex spreadsheet before they can implement the change in business rules. Doing it with script (VBA or Google Script) is just as error-prone, and reduces the number of people who can make any changes even moreso. The biggest issue is that putting business logic in the scope of a single spreadsheet means the logic must be cloned for every report ever produced. This becomes a maintenance nightmare if your business logic evolves, as it always does, sometimes evern before a project is completed.

ETL Tools

NEXT Analytics packaging is easier than buying a formal ETL tool like Matillion because there’s nothing to learn, you get the fully processed data set, and it’s ready to use in just 24 hours.

This is a great way to get started and, if you need more, customization services are available at far less cost and time than you having to learn a new ETL product and implement it’s functions to match your needs. Just tell us what you need, and we get it done. Rapidly, and cost-effectively.

If you are sure you need an ETL tool such as Matillion, then that’s great. Let the NEXT Analytics business rules engine pull data from the database tables that it generates. There are stiill numerous value-adds, things that NEXT can do that Matillion can’t.

The NEXT Analytics Business Rules Engine — What kinds of things can you ask for?

Filtering to remove unwanted data.

Text, dates, and numeric expressions all can be iteratively applied to get at just the data you care about.

Convert tables to crosstab view (pivoted data). See dates as a trend. See dimensions as segments. Compute valuable KPIs from pivoted data.

Integrate the data with query results from databases from operational systems

Make comparing current period data with prior period data super-easy.

Is there something you need that you don’t see in the list? The software probably does what you need. Contact support@nextanalytics.com and ask how what you need can be done.

How Does it Work?

The NEXT Analytics engine downloads data and processes it into report developer friendly format. As a report developer, you’ll be able to use the processed data directly in your charts and tables. This is quicker, easier and more reliable than doing it yourself with scripts and spreadsheet functions. Use our engine, and in 24 hours, you’ll have something that would take you at least a week doing it “the hard way”. You’ll be able to say you already completed a large chunk of your project’s tasks if you offload data conversion and processing to our engine.

The engine makes things like period comparisons and custom KPIs instantly usable and much quicker and easier for the report developer. Being server-based and automated makes the whole process less vulnerable to IT and related download issues and creates less dependency on the reporting developer ensuring someone is trained to perform manual operations at critical times.

The data is updated each day, after midnight passes. This is fully automatic. No more hanging around on Sunday nights to make sure the data updates went through smoothly for the Monday meetings or month end reports. All of your reporting can assume it’s working with the latest data and everybody who looks at the reports will be seeing the same results at all times.

Your results will be much better if you use a SQL connector to already processed data. Google Data Studio, Microsoft Power BI, Google Sheets, and Excel all support a SQL connector and downloading.

Consultancy Services for Customization

Working with already processed tables greatly accelerates the time it takes for you to prepare custom reports and dashboards.

If you need some specialized converstions, KPI creation, custom aggregations, then consider using our consultancy service.

Create dynamic hierarchy. For example, you can combine countries into sales regions.

Create crosstab views (aka Pivots), putting dates on the column axis, automatically rolling them forward. Followed by sorting and ranking on the the most recent time period, then adding a calculation to compare the most recent period to the prior period, and same period a year ago.

Create crosstab views (aka Pivots) putting multi-dimensions on row axis, and a single segmenting dimension on the column axis. This shows patterns and trends and outliers.

Create tables that show rank, standard deviations, top N by % and cumulative sums.

Our Consultancy Service can also support getting data from proprietary sources and database connections. It can also send the data to customer-owned databases, remotely.